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A Study on Compression Techniques for off-the-person Electrocardiogram Signals

机译:离体心电图信号的压缩技术研究

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The compression of Electrocardiography (ECG) signals acquired in off-the-person scenarios requires methods that cope with noise and other impairments on the acquisition process. In this paper, after a brief review of common on-the-person ECG signal compression algorithms, we propose and evaluate techniques for this compression task with off-the-person acquired signals, in both lossy and lossless scenarios, evaluated with standard metrics. Our experimental results show that the joint use of Linear Predictive Coding and Lempel-Ziv-Welch is an adequate lossless approach, and the amplitude scaling followed by the Discrete Wavelet Transform achieves the best compression ratio, with a small distortion, among the lossy techniques.
机译:在非现场情况下采集的心电图(ECG)信号的压缩要求采用应对噪声和采集过程中其他障碍的方法。在本文中,在简要回顾了常见的人体ECG信号压缩算法后,我们提出并评估了在有损和无损情况下使用标准度量进行评估的,具有非现场获取信号的压缩任务的技术。我们的实验结果表明,将线性预测编码和Lempel-Ziv-Welch结合使用是一种适当的无损方法,在有损技术中,采用离散小波变换进行幅度缩放后可获得最佳压缩比,且失真较小。

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